In this work we combine aspects of implicit learning with novelty search in an evolutionary algorithm with the aim to automatically generate melodies with improvisational flavour. Using Markov chains, the technique we present combines implicit statistical knowledge, extracted from musical corpora, with an adaptive novelty search mechanism. The algorithm is described along with the main design choices. Preliminary results are shown in two different musical contexts: Irish music and counterpoint compositions.
Evolutionary Music: Statistical Learning and Novelty for Automatic Improvisation / Barbaresi M.; Roli A.. - STAMPA. - 1722:(2022), pp. 172-183. (Intervento presentato al convegno WIVACE 2021 tenutosi a Winterthur nel September 15-17, 2021) [10.1007/978-3-031-23929-8_17].
Evolutionary Music: Statistical Learning and Novelty for Automatic Improvisation
Barbaresi M.;Roli A.
2022
Abstract
In this work we combine aspects of implicit learning with novelty search in an evolutionary algorithm with the aim to automatically generate melodies with improvisational flavour. Using Markov chains, the technique we present combines implicit statistical knowledge, extracted from musical corpora, with an adaptive novelty search mechanism. The algorithm is described along with the main design choices. Preliminary results are shown in two different musical contexts: Irish music and counterpoint compositions.| File | Dimensione | Formato | |
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